ArticleJournal of the American Geriatrics Society2025
Application of an Electronic Frailty Index to Identify High-Risk Older Adults Using Electronic Health Record Data.
Article in Journal of the American Geriatrics Society, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Hearing Aid Use Attenuates the Association Between Hearing Loss and Frailty: A 2003-2018 NHANES Cross Sectional Analysis.Journal of the American Geriatrics Society · 2026Article
- The Association of an Electronic Frailty Index with Glaucoma Shunt Outcomes.Geriatrics (Basel, Switzerland) · 2026Article
- Characterization of orthogeriatric care models and association with mortality and health-economic outcomes in patients with hip fractures: a retrospective cohort study from Germany.BMC geriatrics · 2026Article
- FI-CGA and eFI-CGA in Frailty Care: a Scoping Review.Canadian geriatrics journal : CGJ · 2026Review
- Longitudinal dynamics of post-diagnosis frailty among older women with ovarian cancer.Gynecologic oncology · 2026Article
- Validation of a Large Language Model Enhanced Frailty Index.Journal of medical systems · 2026Article
- Trajectories of frailty, grip strength and gait speed preceding dementia: a nested case-control study.Age and ageing · 2026Article
- Evaluating Frailty Index Integrity: Insights from an International Network Study.medRxiv : the preprint server for health sciences · 2026Article
- Frailty, Pitavastatin, and Major Adverse Cardiovascular Events Among People With HIV.JACC. Advances · 2025Article
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
backgroundMeasurement of frailty is limited in clinical practice. Existing electronic frailty indices (eFIs) are derived from routine primary care encounters, with near-complete health condition capture. We aimed to develop an eFI from routinely collected clinical data and evaluate its performance in older adults without complete health condition capture.
methodsUsing Electronic Health Record (EHR) data from an integrated regional health system, we created a cohort of patients who were ≥ 60 years on January 1, 2017 with two outpatient encounters in 3 years prior or one outpatient encounter in 2 years prior. We developed an eFI based on 31 age-related deficits identified using diagnostic and procedure codes. Frailty status was categorized as robust (eFI < 0.1), prefrail (0.1-0.2), frail (0.2-0.3), and very frail (> 0.3). We estimated cumulative incidence of mortality, acute care visits and readmissions by frailty, and fit Cox proportional hazards models. We repeated analyses in a sub-cohort of patients who receive primary care in the system.
resultsAmong 518,449 patients, 43% were male with a mean age of 72 years; 73% were robust, 16% were pre-frail, 7% were frail, and 4% were very frail. Very frail older adults had a significantly higher risk for mortality (HR: 4.1, 95% CI: 4.0-4.3), acute care visits (HR: 5.5, 95% CI: 5.4-5.6), and 90-day readmissions (HR: 2.1, 95% CI: 2.1-2.2) than robust older adults. In a primary care sub-cohort, while prevalence of deficits was higher, associations with outcomes were similar.
conclusionsThis eFI identified older adults at increased risk for adverse health outcomes even when data from routine primary care visits were not available. This tool can be integrated into EHRs for frailty assessment at scale.
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